// Use this for initialization void Start() { tutorial_active = false; source = GetComponent <AudioSource>(); initial_node = nodeManager.GetCurrentNode(); next_node = nodeManager.GetNextNode(); evo_controller = GetComponent <EvolutionController>(); transform.position = initial_node.transform.position; initial_position = initial_node.transform.position; next_position = next_node.transform.position; //Update Arrow direction target_controller.SetTarget(next_node.transform); //Set camera at the initial position camera_go.GetComponent <CameraController>().MoveCamera(transform); //Reset HUD DisablePowerUpHUD(PoweUpType.METAL); DisablePowerUpHUD(PoweUpType.SLOW); DisablePowerUpHUD(PoweUpType.STAR); script_star.GetComponent <ScrollingUVs_Layers>().enabled = false; if (startGame) { UI_Menu.GetComponent <UI_Game>().PlayGame(); } }
public void TestMethod2() { var controller = new EvolutionController(); var response = controller.GetByID("x", 1, 1, 0, 1, 75); Assert.IsTrue(response.result > 0); }
void Awake() { Application.targetFrameRate = 60; Time.timeScale = 1; players = new List <PlayerMode>(11); terrains = new Dictionary <TerrainPosition, TerrainGeneration>(); particles = new List <ParticleSystem>(11); cam = Camera.main.GetComponent <CameraFollow>(); evolutionManager = GetComponent <EvolutionController>(); tests = 0; }
/// <summary> /// Adds the agent to the team if requested. /// </summary> private void Start() { if (m_AddToTeam) { TeamManager.AddTeamMember(gameObject, m_TeamIndex); } // Genetic Algorithm initialize evolver = GameObject.Find("Evolution Controller").GetComponent <EvolutionController>(); playerName = this.gameObject.name; phenoType = evolver.GetPhenoType(playerName); }
public void Start() { if (EvolutionControler == null) { Debug.Log("EvolutionController not set - trying to get it from this gameObject."); EvolutionControler = GetComponent <EvolutionController>(); if (EvolutionControler == null) { Debug.LogError("EvolutionController still not set! Disableing."); enabled = false; return; } return; } }
// Use this for initialization void Start() { myTimers = this.GetComponent <Timers>(); myMovement = this.GetComponent <Movement>(); myAnimator = this.GetComponent <Animator>(); myImage = this.GetComponent <Image>(); myAnimController = this.GetComponent <AnimationController>(); myEvolutionController = this.GetComponent <EvolutionController>(); ExpRequirements = new int[6] { 10, 20, 30, 40, 50, 60 }; //to be defined in json in future uiValues = new List <string>() { m_name, m_hunger.ToString(), m_experience.ToString() }; }
// Use this for initialization void Start() { Screen.SetResolution(80, 80, false); Application.targetFrameRate = 15; evolver = GameObject.Find("Evolution Controller").GetComponent <EvolutionController>(); evoManager = new EvolutionInfoManager(); evoManager.ReadInfo(); if (evoManager.Initial()) { // The first game of the first iteration evoManager.Population = evolver.InitializeRandomPopulation(evoManager.N); evoManager.InitializePopulationQueue(); evoManager.WritePopulation("population.csv"); } else if (evoManager.SelectBest()) { evoManager.ReadPopulation("population.csv"); List <PhenoType> best = Selection(); evoManager.Population = best; evoManager.WritePopulation("prev-population.csv"); evoManager.ChildPopulation = GenerateOffspring(); evoManager.Population = evoManager.ChildPopulation; evoManager.InitializePopulationQueue(); } else if (evoManager.EvaluateOffspring()) { evoManager.ReadPopulation("population.csv"); evoManager.WritePopulation("prev-population.csv"); evoManager.ChildPopulation = GenerateOffspring(); evoManager.Population = evoManager.ChildPopulation; evoManager.InitializePopulationQueue(); } else { evoManager.ReadPopulation("population.csv"); evoManager.ReadPopulationQueue(); } PlayGame(); }
static void TestGeneticAlgorithm() { string target = "Be or not to be?"; IEvolutionController evolutionController = new EvolutionController(target); Population population = new Population(evolutionController, 300); population.MutationChance = 10; population.CurrentGeneration.Evaluate(); while (true) { ReadKey(); population.CurrentGeneration.Evaluate(); IDna db = population.CurrentGeneration.Best; WriteLine(new string(db.GetGenes() as char[]) + " ||| " + db.Fitness); population.CreateNewGeneration(); } }
bool[] reachedMarker; //if a particular marker has been reached, true. Same order and size as goalmarkers // Use this for initialization void Start() { rb = GetComponent <Rigidbody2D>(); rand = new System.Random(Guid.NewGuid().GetHashCode()); initialPos = transform.position; ec = GameObject.Find("EvolutionController").GetComponent <EvolutionController>(); //initialize square with ec data maxSteps = ec.GetCurrMaxSteps(); mutationRate = ec.GetMutationRate(); currStep = 0; currDelay = 0; //get initial list of movements //if not a square loaded from disk if (!loadedSquare) { InitializeMovements(); } }
void Update() { if (Input.GetButtonUp("AI_ON")) { AIEnablied = true; brain = EvolutionController.CreateNeuralNet(evaluator); brain.setWeights(new Queue <double>(generateRandomWeights(brain.extractWeights().Count))); } if (AIEnablied) { setNeuralInputs(); List <double> output = brain.calculateOutput(); for (int i = 0; i < output.Count; ++i) { float newThrottle = output[i] < 0 ? 0 : (float)output[i]; if (newThrottle > 1.0f) { newThrottle = 1.0f; } thrusterControllers[i].throttle = newThrottle; } } else { // if (Input.GetButton("Jump")) { // foreach (ThrusterController thrusterController in thrusterControllers) { // thrusterController.firing = true; // } // } else { // foreach (ThrusterController thrusterController in thrusterControllers) { // thrusterController.firing = false; // } // } } }
// Use this for initialization void Start() { ec = GameObject.Find("EvolutionController").GetComponent <EvolutionController>(); stepsText = this.GetComponent <Text>(); }
// Use this for initialization void Start() { text = transform.GetChild(0).GetComponent <Text>(); ec = GameObject.Find("EvolutionController").GetComponent <EvolutionController>(); }